In [157]:
def cal_lasting(ddl,launch):
res = int(ddl) - int(launch)
return list([res])
def dcTransformMapper(elem):
if elem == 'False':
return [0]
else:
return [1]
def splitMapper(elem):
return htf.transform(elem)
from pyspark.sql import Row
from pyspark.ml.linalg import Vectors,DenseVector
from pyspark.ml.feature import HashingTF,IDF,Tokenizer,RegexTokenizer,VectorAssembler
# def f(x):
# rel = {}
# rel['final_status'] = str(x[4])
# rel['features'] = Vectors.dense(float(x[0]),float(x[1]),float(x[2]),float(x[3]))
# return rel
import csv
# remove first row(header)
trainKickstarter = sc.textFile("funding-successful-projects-on-kickstarter/train.csv")
trainHeader = trainKickstarter.first()
trainKickstarter = trainKickstarter.filter(lambda line: line != trainHeader).mapPartitions(lambda x: csv.reader(x))
# print(trainKickstarter.take(10))
# Data Transformations and filter lines with empty strings
trainKickstarter=trainKickstarter.map(lambda line: line[3:5]+dcTransformMapper(line[5])+line[6:7]+cal_lasting(line[8],line[11])+line[12:14])
# print(trainKickstarter.take(10))
# Transfer RDD to DataFrame
trainKickstarter = spark.createDataFrame(trainKickstarter).toDF('goal','key','disable_communication','country','lasting_time','backers','final_status')
# trainKickstarter.show(10)
# -------- Deal with Keywords Attribute--------
reTokenizer = RegexTokenizer(inputCol="key", outputCol="keywords", pattern ='\\W')
wordsData = reTokenizer.transform(trainKickstarter)
# wordsData.show(10)
hashingTF = HashingTF(inputCol="keywords", outputCol="rawKeywords", numFeatures=11)
featurizedData = hashingTF.transform(wordsData)
# featurizedData.show(10)
idf = IDF(inputCol="rawKeywords", outputCol="Keywords")
idfModel = idf.fit(featurizedData)
trainKickstarter = idfModel.transform(featurizedData)
# trainKickstarter.select("final_status", "Keywords").show(10)
# -------- Deal with Country Attribute--------
tokenizer = Tokenizer(inputCol="country", outputCol="countries")
wordsData = tokenizer.transform(trainKickstarter)
# wordsData.show(10)
hashingTF = HashingTF(inputCol="countries", outputCol="rawCountries", numFeatures=11)
featurizedData = hashingTF.transform(wordsData)
# featurizedData.show(10)
idf = IDF(inputCol="rawCountries", outputCol="Countries")
idfModel = idf.fit(featurizedData)
trainKickstarter = idfModel.transform(featurizedData)
# trainKickstarter.select("final_status", "Countries").show(10)
# # -------- Deal with Currency Attribute--------
# tokenizer = Tokenizer(inputCol="currency", outputCol="currencies")
# wordsData = tokenizer.transform(trainKickstarter)
# # wordsData.show(10)
# hashingTF = HashingTF(inputCol="currencies", outputCol="rawCurrencies", numFeatures=11)
# featurizedData = hashingTF.transform(wordsData)
# # featurizedData.show(10)
# idf = IDF(inputCol="rawCurrencies", outputCol="Currency")
# idfModel = idf.fit(featurizedData)
# trainKickstarter = idfModel.transform(featurizedData)
# trainKickstarter.select("final_status", "Currency").show(10)
# Attributes Type Casting
trainKickstarter = trainKickstarter.withColumn('goal',trainKickstarter.goal.cast('float')).withColumn('disable_communication',trainKickstarter.disable_communication.cast('float')).withColumn('lasting_time',trainKickstarter.lasting_time.cast('float')).withColumn('backers',trainKickstarter.backers.cast('float'))
# Combine all the Vectors
vecAssembler = VectorAssembler(inputCols=["goal","Keywords", "disable_communication","Countries", "lasting_time", "backers"], outputCol="features")
trainKickstarter = vecAssembler.transform(trainKickstarter)
trainKickstarter.select('final_status',"goal","key", "disable_communication",'country', "lasting_time", "backers").show(10)
# trainKickstarter.select('featuress').show(10)
trainKickstarter.printSchema()
+------------+------+--------------------+---------------------+-------+------------+-------+ |final_status| goal| key|disable_communication|country|lasting_time|backers| +------------+------+--------------------+---------------------+-------+------------+-------+ | 1| 20.0| drawing-for-dollars| 1.0| US| 731276.0| 3.0| | 0| 300.0|sponsor-dereck-bl...| 1.0| US| 1453408.0| 2.0| | 0| 30.0| mr-squiggles| 1.0| US| 863162.0| 0.0| | 1| 500.0|help-me-write-my-...| 1.0| US| 2589010.0| 18.0| | 0|2000.0|support-casting-m...| 1.0| US| 2589339.0| 1.0| | 0| 700.0| daily-digest| 1.0| US| 2351132.0| 14.0| | 0| 250.0|igoozex-free-ipho...| 1.0| US| 2135692.0| 2.0| | 1|1000.0|drive-a-faster-ca...| 1.0| US| 2617709.0| 32.0| | 0|5000.0|lostles-at-tinys-...| 1.0| US| 2783499.0| 44.0| | 0|3500.0|choose-your-own-a...| 1.0| US| 2673080.0| 18.0| +------------+------+--------------------+---------------------+-------+------------+-------+ only showing top 10 rows root |-- goal: float (nullable = true) |-- key: string (nullable = true) |-- disable_communication: float (nullable = true) |-- country: string (nullable = true) |-- lasting_time: float (nullable = true) |-- backers: float (nullable = true) |-- final_status: string (nullable = true) |-- Keywords: vector (nullable = true) |-- rawKeywords: vector (nullable = true) |-- Countries: vector (nullable = true) |-- rawCountries: vector (nullable = true) |-- features: vector (nullable = true)
In [161]:
# RandomForest Model
from pyspark.ml import Pipeline
from pyspark.ml.feature import IndexToString,StringIndexer,VectorIndexer
from pyspark.ml.classification import RandomForestClassifier
import time
startTime = time.time()
# Index labels, adding metadata to the label column.
# Fit on whole dataset to include all labels in index.
labelIndexer = StringIndexer(inputCol="final_status", outputCol="indexedLabel").fit(trainKickstarter)
# labelIndexer = StringIndexer().setInputCol("label").setOutputCol("indexedLabel").fit(trainKickstarter)
# Automatically identify categorical features, and index them.
# featureIndexer = VectorIndexer(inputCol="featuress", outputCol="indexedFeatures").fit(trainKickstarter)
# featureIndexer = VectorIndexer().setInputCol("features").setOutputCol("indexedFeatures").fit(trainKickstarter)
# Split the data into training and test sets (30% held out for testing)
(trainingData, testData) = trainKickstarter.randomSplit([0.7, 0.3])
# Train a RandomForest model.
rf = RandomForestClassifier(labelCol="indexedLabel", featuresCol="features", numTrees=10)
# Convert indexed labels back to original labels.
labelConverter = IndexToString(inputCol="prediction", outputCol="predictedLabel",labels=labelIndexer.labels)
# Chain indexers and forest in a Pipeline
Pipeline = Pipeline().setStages([labelIndexer,rf, labelConverter])
# Train model. This also runs the indexers.
PipelineModel = Pipeline.fit(trainingData)
endTime = time.time()
executeTime = endTime - startTime
print ('Execution Time For Random Forest = %s' % str(executeTime) + ' Seconds\n')
# Make predictions.
Predictions = PipelineModel.transform(testData)
Predictions.select("predictedLabel", "final_status").show(10)
preRel = Predictions.select("predictedLabel", "final_status", "features", "probability").collect()
print('''final_status --> prob = [prob_0,prob_1], predicted_final_status''')
for item in preRel:
print(str(item['final_status'])+' -->prob = '+str(item['probability'])+', predicted_final_status: '+str(item['predictedLabel']))
Execution Time For Random Forest = 10.085039138793945 Seconds +--------------+------------+ |predictedLabel|final_status| +--------------+------------+ | 0| 0| | 0| 0| | 1| 1| | 1| 1| | 0| 1| | 0| 1| | 0| 1| | 1| 1| | 1| 1| | 0| 1| +--------------+------------+ only showing top 10 rows final_status --> prob = [prob_0,prob_1], predicted_final_status 0 -->prob = [0.924717992216601,0.07528200778339891], predicted_final_status: 0 0 -->prob = [0.8908947790799961,0.10910522092000378], predicted_final_status: 0 1 -->prob = [0.21953481513438394,0.780465184865616], predicted_final_status: 1 1 -->prob = [0.23681953058110022,0.7631804694188997], predicted_final_status: 1 1 -->prob = [0.8101563752090866,0.18984362479091343], predicted_final_status: 0 1 -->prob = [0.7277660664774012,0.27223393352259884], predicted_final_status: 0 1 -->prob = [0.7955602181940168,0.20443978180598324], predicted_final_status: 0 1 -->prob = [0.28315770281380626,0.7168422971861937], predicted_final_status: 1 1 -->prob = [0.4900354668007482,0.5099645331992517], predicted_final_status: 1 1 -->prob = [0.8562291073597458,0.14377089264025422], predicted_final_status: 0 1 -->prob = [0.9108397934846151,0.08916020651538484], predicted_final_status: 0 1 -->prob = [0.7902021748405633,0.2097978251594367], predicted_final_status: 0 0 -->prob = [0.8713510145066902,0.12864898549330978], predicted_final_status: 0 1 -->prob = [0.7815732921443381,0.21842670785566187], predicted_final_status: 0 1 -->prob = [0.8887547690540776,0.11124523094592229], predicted_final_status: 0 1 -->prob = [0.8222780832190285,0.1777219167809714], predicted_final_status: 0 0 -->prob = [0.8941488467822972,0.10585115321770278], predicted_final_status: 0 1 -->prob = [0.6301883589542241,0.3698116410457759], predicted_final_status: 0 0 -->prob = [0.8974144979329225,0.10258550206707759], predicted_final_status: 0 1 -->prob = [0.3148952146868543,0.6851047853131458], predicted_final_status: 1 1 -->prob = [0.8391714087800148,0.16082859121998527], predicted_final_status: 0 0 -->prob = [0.8316834189416087,0.16831658105839137], predicted_final_status: 0 1 -->prob = [0.8632534982015049,0.13674650179849518], predicted_final_status: 0 1 -->prob = [0.7980755334185313,0.20192446658146856], predicted_final_status: 0 1 -->prob = [0.8506137092823688,0.1493862907176312], predicted_final_status: 0 1 -->prob = [0.2868211651601393,0.7131788348398607], predicted_final_status: 1 0 -->prob = [0.8861500284738575,0.11384997152614247], predicted_final_status: 0 0 -->prob = [0.8523249810365179,0.14767501896348217], predicted_final_status: 0 0 -->prob = [0.891118191493273,0.10888180850672705], predicted_final_status: 0 1 -->prob = [0.3481732610792988,0.6518267389207011], predicted_final_status: 1 1 -->prob = [0.46353303043393596,0.536466969566064], predicted_final_status: 1 1 -->prob = [0.6126910119041489,0.3873089880958511], predicted_final_status: 0 0 -->prob = [0.924717992216601,0.07528200778339891], predicted_final_status: 0 1 -->prob = [0.7836497076202454,0.21635029237975453], predicted_final_status: 0 1 -->prob = [0.6217147329350612,0.37828526706493876], predicted_final_status: 0 1 -->prob = [0.3989791651887963,0.6010208348112037], predicted_final_status: 1 0 -->prob = [0.8784031579522263,0.12159684204777362], predicted_final_status: 0 1 -->prob = [0.37150496225641466,0.6284950377435854], predicted_final_status: 1 0 -->prob = [0.893541611397757,0.10645838860224295], predicted_final_status: 0 1 -->prob = [0.2844216067749544,0.7155783932250455], predicted_final_status: 1 0 -->prob = [0.8702559327211018,0.12974406727889812], predicted_final_status: 0 1 -->prob = [0.9124503021155513,0.08754969788444866], predicted_final_status: 0 1 -->prob = [0.5772681408460365,0.42273185915396355], predicted_final_status: 0 1 -->prob = [0.7084140887088605,0.29158591129113953], predicted_final_status: 0 0 -->prob = [0.9207101882735721,0.07928981172642793], predicted_final_status: 0 1 -->prob = [0.9190688167135468,0.08093118328645328], predicted_final_status: 0 1 -->prob = [0.8926684316394923,0.1073315683605077], predicted_final_status: 0 0 -->prob = [0.8127166605628193,0.1872833394371807], predicted_final_status: 0 1 -->prob = [0.8901998170142233,0.10980018298577661], predicted_final_status: 0 0 -->prob = [0.8714735042597217,0.12852649574027836], predicted_final_status: 0 0 -->prob = [0.8525331281803693,0.14746687181963078], predicted_final_status: 0 1 -->prob = [0.8461933349065703,0.15380666509342966], predicted_final_status: 0 1 -->prob = [0.6784709269044746,0.3215290730955254], predicted_final_status: 0 1 -->prob = [0.911303773547742,0.08869622645225808], predicted_final_status: 0 1 -->prob = [0.8158784106251685,0.1841215893748314], predicted_final_status: 0 0 -->prob = [0.8771426867076846,0.1228573132923155], predicted_final_status: 0 1 -->prob = [0.5648001361513291,0.435199863848671], predicted_final_status: 0 1 -->prob = [0.3172073320388693,0.6827926679611307], predicted_final_status: 1 0 -->prob = [0.8180373719494552,0.1819626280505448], predicted_final_status: 0 0 -->prob = [0.8572992014187079,0.14270079858129214], predicted_final_status: 0 1 -->prob = [0.37643673784742304,0.6235632621525768], predicted_final_status: 1 0 -->prob = [0.9078385331972054,0.09216146680279462], predicted_final_status: 0 1 -->prob = [0.4576365995294319,0.5423634004705681], predicted_final_status: 1 1 -->prob = [0.8709284312885088,0.12907156871149117], predicted_final_status: 0 1 -->prob = [0.20088653712461318,0.7991134628753868], predicted_final_status: 1 0 -->prob = [0.8904232294275001,0.10957677057249988], predicted_final_status: 0 0 -->prob = [0.9177501753766519,0.08224982462334805], predicted_final_status: 0 1 -->prob = [0.7396827975723107,0.2603172024276893], predicted_final_status: 0 0 -->prob = [0.908493133619718,0.09150686638028196], predicted_final_status: 0 0 -->prob = [0.8695953875083224,0.13040461249167742], predicted_final_status: 0 1 -->prob = [0.7243828369773623,0.2756171630226377], predicted_final_status: 0 1 -->prob = [0.269794723425978,0.7302052765740219], predicted_final_status: 1 0 -->prob = [0.8470228306238408,0.1529771693761593], predicted_final_status: 0 1 -->prob = [0.3862278950203361,0.6137721049796638], predicted_final_status: 1 1 -->prob = [0.2657307923248454,0.7342692076751546], predicted_final_status: 1 1 -->prob = [0.735184250982276,0.26481574901772403], predicted_final_status: 0 0 -->prob = [0.9238148830069768,0.07618511699302313], predicted_final_status: 0 1 -->prob = [0.846919219688876,0.153080780311124], predicted_final_status: 0 1 -->prob = [0.6784709269044746,0.3215290730955254], predicted_final_status: 0 0 -->prob = [0.7538269935350373,0.24617300646496254], predicted_final_status: 0 1 -->prob = [0.5628435578637517,0.43715644213624827], predicted_final_status: 0 1 -->prob = [0.20240671360410056,0.7975932863958993], predicted_final_status: 1 0 -->prob = [0.9134873609468166,0.08651263905318349], predicted_final_status: 0 1 -->prob = [0.3107607499490898,0.6892392500509101], predicted_final_status: 1 1 -->prob = [0.8412545788500992,0.15874542114990078], predicted_final_status: 0 1 -->prob = [0.912896697171911,0.08710330282808891], predicted_final_status: 0 1 -->prob = [0.3180516795899334,0.6819483204100666], predicted_final_status: 1 0 -->prob = [0.78363833400244,0.21636166599755996], predicted_final_status: 0 1 -->prob = [0.8806652750633013,0.11933472493669868], predicted_final_status: 0 0 -->prob = [0.9134783206435537,0.0865216793564463], predicted_final_status: 0 1 -->prob = [0.7008117842542874,0.29918821574571264], predicted_final_status: 0 0 -->prob = [0.8417380170578046,0.15826198294219537], predicted_final_status: 0 0 -->prob = [0.915264418238886,0.08473558176111404], predicted_final_status: 0 0 -->prob = [0.9227243957588419,0.07727560424115804], predicted_final_status: 0 0 -->prob = [0.8394029423076864,0.16059705769231364], predicted_final_status: 0 1 -->prob = [0.6326947683388822,0.3673052316611179], predicted_final_status: 0 1 -->prob = [0.7927303064655249,0.20726969353447508], predicted_final_status: 0 1 -->prob = [0.7958902657148382,0.2041097342851618], predicted_final_status: 0 0 -->prob = [0.8861500284738575,0.11384997152614247], predicted_final_status: 0 1 -->prob = [0.8727339755042636,0.12726602449573646], predicted_final_status: 0 0 -->prob = [0.8941488467822972,0.10585115321770278], predicted_final_status: 0 1 -->prob = [0.5168901834151087,0.4831098165848912], predicted_final_status: 0 1 -->prob = [0.458742070577958,0.541257929422042], predicted_final_status: 1 1 -->prob = [0.3226579669747799,0.6773420330252201], predicted_final_status: 1 0 -->prob = [0.8443932726872317,0.15560672731276817], predicted_final_status: 0 0 -->prob = [0.9184525410257438,0.08154745897425628], predicted_final_status: 0 0 -->prob = [0.7639707605506014,0.23602923944939863], predicted_final_status: 0 1 -->prob = [0.6092393622020699,0.39076063779793013], predicted_final_status: 0 0 -->prob = [0.8471233603016847,0.15287663969831525], predicted_final_status: 0 0 -->prob = [0.8816590599552623,0.11834094004473776], predicted_final_status: 0 1 -->prob = [0.23277881955798635,0.7672211804420137], predicted_final_status: 1 1 -->prob = [0.5714905063059237,0.4285094936940763], predicted_final_status: 0 1 -->prob = [0.2825871886385515,0.7174128113614485], predicted_final_status: 1 0 -->prob = [0.6260214381614805,0.3739785618385196], predicted_final_status: 0 0 -->prob = [0.8417380170578046,0.15826198294219537], predicted_final_status: 0 0 -->prob = [0.8514147298166573,0.14858527018334264], predicted_final_status: 0 1 -->prob = [0.2338385098914723,0.7661614901085277], predicted_final_status: 1 1 -->prob = [0.8115860518479655,0.18841394815203452], predicted_final_status: 0 1 -->prob = [0.9190488097686382,0.08095119023136176], predicted_final_status: 0 1 -->prob = [0.4846715459374972,0.5153284540625029], predicted_final_status: 1 1 -->prob = [0.8548048858978797,0.14519511410212035], predicted_final_status: 0 1 -->prob = [0.3097645617028788,0.6902354382971211], predicted_final_status: 1 1 -->prob = [0.385619158373649,0.6143808416263509], predicted_final_status: 1 1 -->prob = [0.29868109391162634,0.7013189060883736], predicted_final_status: 1 1 -->prob = [0.7269954715369089,0.27300452846309103], predicted_final_status: 0 0 -->prob = [0.8795758898851778,0.12042411011482224], predicted_final_status: 0 1 -->prob = [0.9140745893864481,0.08592541061355177], predicted_final_status: 0 1 -->prob = [0.30674785368502067,0.6932521463149792], predicted_final_status: 1 0 -->prob = [0.9019054664515177,0.09809453354848227], predicted_final_status: 0 1 -->prob = [0.850165921744493,0.14983407825550704], predicted_final_status: 0 0 -->prob = [0.9082923900591856,0.09170760994081442], predicted_final_status: 0 0 -->prob = [0.8586205408472244,0.14137945915277556], predicted_final_status: 0 1 -->prob = [0.29820366803560167,0.7017963319643983], predicted_final_status: 1 1 -->prob = [0.35947708698421166,0.6405229130157885], predicted_final_status: 1 1 -->prob = [0.7932135583291196,0.20678644167088037], predicted_final_status: 0 1 -->prob = [0.7142545499265708,0.2857454500734293], predicted_final_status: 0 1 -->prob = [0.7355928264139143,0.2644071735860856], predicted_final_status: 0 1 -->prob = [0.6910445525103039,0.30895544748969606], predicted_final_status: 0 1 -->prob = [0.7141810270587079,0.2858189729412922], predicted_final_status: 0 1 -->prob = [0.42035052783318105,0.579649472166819], predicted_final_status: 1 1 -->prob = [0.7610755317369307,0.23892446826306948], predicted_final_status: 0 1 -->prob = [0.5177021196924887,0.4822978803075114], predicted_final_status: 0 1 -->prob = [0.32265302895983006,0.6773469710401699], predicted_final_status: 1 0 -->prob = [0.8914202602839211,0.10857973971607894], predicted_final_status: 0 0 -->prob = [0.839141977219135,0.16085802278086492], predicted_final_status: 0 1 -->prob = [0.8547630656851951,0.1452369343148049], predicted_final_status: 0 1 -->prob = [0.5600168335965791,0.43998316640342094], predicted_final_status: 0 1 -->prob = [0.325425600238016,0.6745743997619841], predicted_final_status: 1 1 -->prob = [0.35914102879128906,0.6408589712087109], predicted_final_status: 1 1 -->prob = [0.6461585606535627,0.35384143934643736], predicted_final_status: 0 1 -->prob = [0.3446498814229039,0.655350118577096], predicted_final_status: 1 1 -->prob = [0.3584583004795861,0.6415416995204138], predicted_final_status: 1 1 -->prob = [0.768170980731349,0.2318290192686509], predicted_final_status: 0 0 -->prob = [0.9095528613037274,0.09044713869627251], predicted_final_status: 0 1 -->prob = [0.2960987778271794,0.7039012221728205], predicted_final_status: 1 0 -->prob = [0.6769370701269619,0.3230629298730381], predicted_final_status: 0 1 -->prob = [0.6458339818144119,0.3541660181855882], predicted_final_status: 0 1 -->prob = [0.5107411624047332,0.4892588375952668], predicted_final_status: 0 1 -->prob = [0.5120886548129325,0.48791134518706747], predicted_final_status: 0 1 -->prob = [0.28453780110989496,0.715462198890105], predicted_final_status: 1 1 -->prob = [0.7613376310561917,0.23866236894380818], predicted_final_status: 0 0 -->prob = [0.9169412706341467,0.08305872936585336], predicted_final_status: 0 1 -->prob = [0.30747283338525894,0.692527166614741], predicted_final_status: 1 1 -->prob = [0.7607791760343898,0.23922082396561023], predicted_final_status: 0 0 -->prob = [0.8864038105614009,0.1135961894385991], predicted_final_status: 0 0 -->prob = [0.8510810355624271,0.14891896443757285], predicted_final_status: 0 1 -->prob = [0.35134749777674956,0.6486525022232503], predicted_final_status: 1 0 -->prob = [0.5341066090462816,0.46589339095371834], predicted_final_status: 0 1 -->prob = [0.6371068008389418,0.36289319916105833], predicted_final_status: 0 0 -->prob = [0.9157947420663373,0.08420525793366278], predicted_final_status: 0 1 -->prob = [0.39931143515194517,0.6006885648480549], 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predicted_final_status: 1 1 -->prob = [0.41701129209194326,0.5829887079080567], predicted_final_status: 1 0 -->prob = [0.6526562377218001,0.34734376227819985], predicted_final_status: 0 1 -->prob = [0.3091034352702281,0.690896564729772], predicted_final_status: 1 0 -->prob = [0.9349425680351711,0.06505743196482888], predicted_final_status: 0 1 -->prob = [0.32285785878697537,0.6771421412130245], predicted_final_status: 1 0 -->prob = [0.9631952920466915,0.036804707953308556], predicted_final_status: 0 1 -->prob = [0.4057074661870305,0.5942925338129694], predicted_final_status: 1 0 -->prob = [0.9090670702329362,0.09093292976706384], predicted_final_status: 0 0 -->prob = [0.8875168553045271,0.11248314469547291], predicted_final_status: 0 1 -->prob = [0.3356886070722062,0.6643113929277938], predicted_final_status: 1 0 -->prob = [0.7332923149910042,0.26670768500899583], predicted_final_status: 0 1 -->prob = [0.3921409151475544,0.6078590848524457], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 1 1 -->prob = [0.34210614208807566,0.6578938579119243], predicted_final_status: 1 1 -->prob = [0.34210614208807566,0.6578938579119243], predicted_final_status: 1 0 -->prob = [0.93756841006029,0.06243158993971], predicted_final_status: 0 0 -->prob = [0.48336937973309413,0.5166306202669059], predicted_final_status: 1 0 -->prob = [0.4153199366033384,0.5846800633966616], predicted_final_status: 1 0 -->prob = [0.40305598946287063,0.5969440105371293], predicted_final_status: 1 0 -->prob = [0.4203690225207035,0.5796309774792965], predicted_final_status: 1 0 -->prob = [0.47286369882658275,0.5271363011734173], predicted_final_status: 1 1 -->prob = [0.8001332211674207,0.19986677883257936], predicted_final_status: 0 1 -->prob = [0.3581060447234415,0.6418939552765585], predicted_final_status: 1 1 -->prob = [0.32151768555961524,0.6784823144403849], predicted_final_status: 1 0 -->prob = [0.8809026324304778,0.11909736756952219], predicted_final_status: 0 1 -->prob = 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predicted_final_status: 1 1 -->prob = [0.40335566085330726,0.5966443391466927], predicted_final_status: 1 1 -->prob = [0.3816594934434234,0.6183405065565766], predicted_final_status: 1 0 -->prob = [0.9077636479459977,0.09223635205400232], predicted_final_status: 0 0 -->prob = [0.9341475424696245,0.06585245753037547], predicted_final_status: 0 1 -->prob = [0.38669669504328585,0.613303304956714], predicted_final_status: 1 0 -->prob = [0.34387430281461745,0.6561256971853826], predicted_final_status: 1 0 -->prob = [0.913987692493446,0.08601230750655395], predicted_final_status: 0 1 -->prob = [0.3916193335132877,0.6083806664867123], predicted_final_status: 1 0 -->prob = [0.9322024357885468,0.06779756421145314], predicted_final_status: 0 0 -->prob = [0.40242314659426776,0.5975768534057322], predicted_final_status: 1 1 -->prob = [0.36249607912930254,0.6375039208706974], predicted_final_status: 1 1 -->prob = [0.3230378620391026,0.6769621379608974], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 0 0 -->prob = [0.9361617499548943,0.0638382500451056], predicted_final_status: 0 0 -->prob = [0.906607510736433,0.09339248926356697], predicted_final_status: 0 0 -->prob = [0.8326217384120824,0.16737826158791755], predicted_final_status: 0 1 -->prob = [0.418312841610469,0.581687158389531], predicted_final_status: 1 0 -->prob = [0.39800052094819854,0.6019994790518014], predicted_final_status: 1 1 -->prob = [0.4607178660181136,0.5392821339818864], predicted_final_status: 1 1 -->prob = [0.345529318385634,0.654470681614366], predicted_final_status: 1 1 -->prob = [0.305644761767613,0.6943552382323871], predicted_final_status: 1 0 -->prob = [0.8892443900836376,0.11075560991636232], predicted_final_status: 0 0 -->prob = [0.8578900980580576,0.14210990194194234], predicted_final_status: 0 0 -->prob = [0.9104078636965024,0.08959213630349762], predicted_final_status: 0 0 -->prob = [0.7408289743683795,0.25917102563162064], predicted_final_status: 0 0 -->prob = 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predicted_final_status: 1 1 -->prob = [0.38669669504328585,0.613303304956714], predicted_final_status: 1 0 -->prob = [0.8759946729979069,0.1240053270020931], predicted_final_status: 0 0 -->prob = [0.41748317747124225,0.5825168225287577], predicted_final_status: 1 1 -->prob = [0.44117531736306825,0.5588246826369319], predicted_final_status: 1 0 -->prob = [0.7591967508088231,0.240803249191177], predicted_final_status: 0 1 -->prob = [0.3265548871594776,0.6734451128405224], predicted_final_status: 1 1 -->prob = [0.5097624497836093,0.4902375502163907], predicted_final_status: 0 0 -->prob = [0.8617782930157615,0.13822170698423847], predicted_final_status: 0 0 -->prob = [0.8812071469977371,0.11879285300226301], predicted_final_status: 0 0 -->prob = [0.4879685258868511,0.512031474113149], predicted_final_status: 1 1 -->prob = [0.7845528680899374,0.21544713191006268], predicted_final_status: 0 0 -->prob = [0.3880405180218731,0.6119594819781269], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 1 0 -->prob = [0.91531995043209,0.08468004956790989], predicted_final_status: 0 1 -->prob = [0.3880405180218731,0.6119594819781269], predicted_final_status: 1 1 -->prob = [0.31946150464938083,0.6805384953506192], predicted_final_status: 1 0 -->prob = [0.8284292570325851,0.17157074296741487], predicted_final_status: 0 0 -->prob = [0.3747700119031851,0.6252299880968148], predicted_final_status: 1 1 -->prob = [0.37556806576075713,0.6244319342392429], predicted_final_status: 1 1 -->prob = [0.3602358577392143,0.6397641422607857], predicted_final_status: 1 0 -->prob = [0.9128972052453111,0.08710279475468885], predicted_final_status: 0 1 -->prob = [0.33352707991219177,0.6664729200878081], predicted_final_status: 1 1 -->prob = [0.5602471194587727,0.4397528805412274], predicted_final_status: 0 0 -->prob = [0.9151438297030106,0.0848561702969893], predicted_final_status: 0 1 -->prob = [0.2985836324235069,0.7014163675764931], predicted_final_status: 1 1 -->prob = 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predicted_final_status: 1 1 -->prob = [0.4534788433417618,0.5465211566582382], predicted_final_status: 1 1 -->prob = [0.3312985327004105,0.6687014672995895], predicted_final_status: 1 1 -->prob = [0.3687627034343529,0.6312372965656471], predicted_final_status: 1 1 -->prob = [0.3265548871594776,0.6734451128405224], predicted_final_status: 1 1 -->prob = [0.3267790129984144,0.6732209870015856], predicted_final_status: 1 0 -->prob = [0.913987692493446,0.08601230750655395], predicted_final_status: 0 1 -->prob = [0.3587369704505874,0.6412630295494125], predicted_final_status: 1 0 -->prob = [0.9363478216437269,0.06365217835627318], predicted_final_status: 0 0 -->prob = [0.8875604943186897,0.11243950568131031], predicted_final_status: 0 0 -->prob = [0.9138203213998439,0.08617967860015616], predicted_final_status: 0 0 -->prob = [0.4418210985064979,0.5581789014935021], predicted_final_status: 1 0 -->prob = [0.35392364358094086,0.6460763564190591], predicted_final_status: 1 1 -->prob = 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predicted_final_status: 1 0 -->prob = [0.9350695723071617,0.06493042769283833], predicted_final_status: 0 1 -->prob = [0.31946150464938083,0.6805384953506192], predicted_final_status: 1 1 -->prob = [0.41981840018184685,0.5801815998181532], predicted_final_status: 1 1 -->prob = [0.8395619465584353,0.16043805344156464], predicted_final_status: 0 0 -->prob = [0.8574182044671087,0.1425817955328914], predicted_final_status: 0 0 -->prob = [0.8566651766926018,0.14333482330739813], predicted_final_status: 0 0 -->prob = [0.44689963764911483,0.5531003623508852], predicted_final_status: 1 0 -->prob = [0.4524368150344517,0.5475631849655483], predicted_final_status: 1 1 -->prob = [0.3531219478092957,0.6468780521907043], predicted_final_status: 1 0 -->prob = [0.4454579956542154,0.5545420043457846], predicted_final_status: 1 1 -->prob = [0.36552236690850687,0.6344776330914932], predicted_final_status: 1 1 -->prob = [0.38317966992291075,0.6168203300770893], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 0 1 -->prob = [0.4048177675921055,0.5951822324078945], predicted_final_status: 1 1 -->prob = [0.3483727663931259,0.651627233606874], predicted_final_status: 1 1 -->prob = [0.3935139416871928,0.6064860583128071], predicted_final_status: 1 0 -->prob = [0.8822151095930438,0.1177848904069561], predicted_final_status: 0 1 -->prob = [0.4406723818722438,0.5593276181277562], predicted_final_status: 1 0 -->prob = [0.8762061412963097,0.12379385870369031], predicted_final_status: 0 1 -->prob = [0.3244987062492432,0.6755012937507568], predicted_final_status: 1 1 -->prob = [0.39921193893414747,0.6007880610658525], predicted_final_status: 1 0 -->prob = [0.537886990308492,0.46211300969150815], predicted_final_status: 0 0 -->prob = [0.43415416974930265,0.5658458302506973], predicted_final_status: 1 0 -->prob = [0.8897581998343931,0.11024180016560688], predicted_final_status: 0 1 -->prob = [0.3691868783258462,0.6308131216741538], predicted_final_status: 1 1 -->prob = 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predicted_final_status: 0 0 -->prob = [0.4660464521826758,0.5339535478173242], predicted_final_status: 1 0 -->prob = [0.9348411503062518,0.0651588496937481], predicted_final_status: 0 0 -->prob = [0.9142294631839551,0.08577053681604481], predicted_final_status: 0 1 -->prob = [0.4153199366033384,0.5846800633966616], predicted_final_status: 1 0 -->prob = [0.9024919737288221,0.09750802627117795], predicted_final_status: 0 1 -->prob = [0.27204490416040883,0.7279550958395912], predicted_final_status: 1 0 -->prob = [0.8969998928618402,0.10300010713815973], predicted_final_status: 0 1 -->prob = [0.3400499611778412,0.6599500388221589], predicted_final_status: 1 0 -->prob = [0.9407387547551245,0.05926124524487549], predicted_final_status: 0 1 -->prob = [0.3265548871594776,0.6734451128405224], predicted_final_status: 1 1 -->prob = [0.38458277665968577,0.6154172233403142], predicted_final_status: 1 0 -->prob = [0.8651857227104081,0.13481427728959183], predicted_final_status: 0 0 -->prob = 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predicted_final_status: 0 0 -->prob = [0.3746009597026293,0.6253990402973707], predicted_final_status: 1 1 -->prob = [0.3805728666738197,0.6194271333261804], predicted_final_status: 1 0 -->prob = [0.9335039509954879,0.06649604900451213], predicted_final_status: 0 0 -->prob = [0.443133300724882,0.556866699275118], predicted_final_status: 1 0 -->prob = [0.910336712502273,0.08966328749772705], predicted_final_status: 0 1 -->prob = [0.47080392654459596,0.5291960734554041], predicted_final_status: 1 0 -->prob = [0.4048177675921055,0.5951822324078945], predicted_final_status: 1 0 -->prob = [0.8585983973117995,0.1414016026882005], predicted_final_status: 0 1 -->prob = [0.2791382866705058,0.7208617133294942], predicted_final_status: 1 1 -->prob = [0.3537620708446116,0.6462379291553885], predicted_final_status: 1 1 -->prob = [0.36867320273789367,0.6313267972621063], predicted_final_status: 1 1 -->prob = [0.31946150464938083,0.6805384953506192], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 1 0 -->prob = [0.4916413772347896,0.5083586227652104], predicted_final_status: 1 1 -->prob = [0.3265548871594776,0.6734451128405224], predicted_final_status: 1 0 -->prob = [0.9092462252541381,0.09075377474586194], predicted_final_status: 0 0 -->prob = [0.8538251300702238,0.14617486992977638], predicted_final_status: 0 0 -->prob = [0.9395826175455598,0.060417382454440116], predicted_final_status: 0 1 -->prob = [0.3826290475840541,0.617370952415946], predicted_final_status: 1 0 -->prob = [0.9384921302974251,0.06150786970257503], predicted_final_status: 0 1 -->prob = [0.33337213380338465,0.6666278661966153], predicted_final_status: 1 0 -->prob = [0.8438731002628248,0.15612689973717525], predicted_final_status: 0 1 -->prob = [0.31021385965470255,0.6897861403452975], predicted_final_status: 1 1 -->prob = [0.25228320583699504,0.747716794163005], predicted_final_status: 1 0 -->prob = [0.9288415332914752,0.07115846670852485], predicted_final_status: 0 0 -->prob = 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predicted_final_status: 1 1 -->prob = [0.4241173598598024,0.5758826401401975], predicted_final_status: 1 0 -->prob = [0.41512037674789093,0.584879623252109], predicted_final_status: 1 1 -->prob = [0.41981840018184685,0.5801815998181532], predicted_final_status: 1 1 -->prob = [0.3768261928134196,0.6231738071865804], predicted_final_status: 1 0 -->prob = [0.7787094565447391,0.22129054345526086], predicted_final_status: 0 1 -->prob = [0.31948821429137897,0.680511785708621], predicted_final_status: 1 1 -->prob = [0.3846405141330514,0.6153594858669486], predicted_final_status: 1 1 -->prob = [0.36876165801117355,0.6312383419888264], predicted_final_status: 1 0 -->prob = [0.3904727309600628,0.6095272690399371], predicted_final_status: 1 0 -->prob = [0.7741280173224768,0.22587198267752323], predicted_final_status: 0 0 -->prob = [0.9009383282884702,0.0990616717115298], predicted_final_status: 0 0 -->prob = [0.4182432198196008,0.5817567801803992], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 1 0 -->prob = [0.8061794757758685,0.19382052422413149], predicted_final_status: 0 0 -->prob = [0.936477922812155,0.06352207718784489], predicted_final_status: 0 0 -->prob = [0.8687571620244011,0.13124283797559894], predicted_final_status: 0 0 -->prob = [0.3468672078217482,0.6531327921782519], predicted_final_status: 1 1 -->prob = [0.8287893836533806,0.17121061634661933], predicted_final_status: 0 1 -->prob = [0.39791931319748974,0.6020806868025101], predicted_final_status: 1 0 -->prob = [0.38669669504328585,0.613303304956714], predicted_final_status: 1 1 -->prob = [0.36022721463689533,0.6397727853631047], predicted_final_status: 1 1 -->prob = [0.3295171699263256,0.6704828300736743], predicted_final_status: 1 0 -->prob = [0.8354960049673018,0.1645039950326981], predicted_final_status: 0 1 -->prob = [0.36022721463689533,0.6397727853631047], predicted_final_status: 1 0 -->prob = [0.42662376250825107,0.5733762374917489], predicted_final_status: 1 1 -->prob = 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predicted_final_status: 1 1 -->prob = [0.35421102266140236,0.6457889773385975], predicted_final_status: 1 0 -->prob = [0.8516038101525641,0.1483961898474358], predicted_final_status: 0 1 -->prob = [0.3285476157856949,0.671452384214305], predicted_final_status: 1 1 -->prob = [0.8237942244418054,0.17620577555819464], predicted_final_status: 0 0 -->prob = [0.8011760373062178,0.19882396269378227], predicted_final_status: 0 1 -->prob = [0.3960241070051394,0.6039758929948605], predicted_final_status: 1 0 -->prob = [0.9326968416525536,0.06730315834744627], predicted_final_status: 0 1 -->prob = [0.3773768151522763,0.6226231848477237], predicted_final_status: 1 0 -->prob = [0.8237942244418054,0.17620577555819464], predicted_final_status: 0 0 -->prob = [0.4248556017817092,0.5751443982182908], predicted_final_status: 1 1 -->prob = [0.4048177675921055,0.5951822324078945], predicted_final_status: 1 0 -->prob = [0.9235218698520278,0.0764781301479723], predicted_final_status: 0 0 -->prob = 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predicted_final_status: 0 1 -->prob = [0.41776221927161233,0.5822377807283876], predicted_final_status: 1 1 -->prob = [0.41981840018184685,0.5801815998181532], predicted_final_status: 1 0 -->prob = [0.8015116670712329,0.19848833292876705], predicted_final_status: 0 0 -->prob = [0.9079582092594155,0.09204179074058455], predicted_final_status: 0 1 -->prob = [0.28523517860385417,0.7147648213961458], predicted_final_status: 1 0 -->prob = [0.4153199366033384,0.5846800633966616], predicted_final_status: 1 0 -->prob = [0.8787123042161286,0.12128769578387148], predicted_final_status: 0 0 -->prob = [0.7367877430715298,0.2632122569284703], predicted_final_status: 0 0 -->prob = [0.7708968635259551,0.22910313647404487], predicted_final_status: 0 1 -->prob = [0.38317966992291075,0.6168203300770893], predicted_final_status: 1 0 -->prob = [0.9303281050678537,0.06967189493214634], predicted_final_status: 0 1 -->prob = [0.3244987062492432,0.6755012937507568], predicted_final_status: 1 1 -->prob = 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predicted_final_status: 0 1 -->prob = [0.36145632306794084,0.638543676932059], predicted_final_status: 1 1 -->prob = [0.32151768555961524,0.6784823144403849], predicted_final_status: 1 0 -->prob = [0.49845862387869655,0.5015413761213035], predicted_final_status: 1 1 -->prob = [0.3519103079830076,0.6480896920169923], predicted_final_status: 1 0 -->prob = [0.41981840018184685,0.5801815998181532], predicted_final_status: 1 1 -->prob = [0.36867320273789367,0.6313267972621063], predicted_final_status: 1 0 -->prob = [0.5634819153606058,0.4365180846393943], predicted_final_status: 0 0 -->prob = [0.9031510920586777,0.09684890794132227], predicted_final_status: 0 0 -->prob = [0.4916413772347896,0.5083586227652104], predicted_final_status: 1 1 -->prob = [0.40700542433380404,0.5929945756661958], predicted_final_status: 1 0 -->prob = [0.9047331800157398,0.09526681998426016], predicted_final_status: 0 0 -->prob = [0.9302624551064239,0.06973754489357606], predicted_final_status: 0 1 -->prob = 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predicted_final_status: 0 1 -->prob = [0.31372340037940005,0.6862765996206], predicted_final_status: 1 1 -->prob = [0.3572314118792096,0.6427685881207903], predicted_final_status: 1 1 -->prob = [0.39090713843810165,0.6090928615618983], predicted_final_status: 1 1 -->prob = [0.3773768151522763,0.6226231848477237], predicted_final_status: 1 1 -->prob = [0.36136836259506083,0.6386316374049392], predicted_final_status: 1 0 -->prob = [0.3537620708446116,0.6462379291553885], predicted_final_status: 1 1 -->prob = [0.33157335083656014,0.6684266491634399], predicted_final_status: 1 0 -->prob = [0.8577975754563006,0.1422024245436993], predicted_final_status: 0 0 -->prob = [0.4153199366033384,0.5846800633966616], predicted_final_status: 1 1 -->prob = [0.31946150464938083,0.6805384953506192], predicted_final_status: 1 0 -->prob = [0.3816594934434234,0.6183405065565766], predicted_final_status: 1 1 -->prob = [0.3220683078984719,0.6779316921015281], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 1 0 -->prob = [0.829359098723554,0.17064090127644596], predicted_final_status: 0 1 -->prob = [0.39090713843810165,0.6090928615618983], predicted_final_status: 1 1 -->prob = [0.37903740679535514,0.6209625932046448], predicted_final_status: 1 0 -->prob = [0.4499291955940382,0.5500708044059618], predicted_final_status: 1 1 -->prob = [0.3107272690176462,0.6892727309823539], predicted_final_status: 1 1 -->prob = [0.37259898359538457,0.6274010164046153], predicted_final_status: 1 0 -->prob = [0.38669669504328585,0.613303304956714], predicted_final_status: 1 0 -->prob = [0.3370689404882133,0.6629310595117868], predicted_final_status: 1 0 -->prob = [0.9049620936618163,0.09503790633818372], predicted_final_status: 0 0 -->prob = [0.3944834958278235,0.6055165041721764], predicted_final_status: 1 0 -->prob = [0.889742321923214,0.11025767807678599], predicted_final_status: 0 1 -->prob = [0.3400979728083394,0.6599020271916605], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 1 0 -->prob = [0.659001096430392,0.3409989035696081], predicted_final_status: 0 1 -->prob = [0.3367723283830102,0.6632276716169898], predicted_final_status: 1 1 -->prob = [0.3447491077265323,0.6552508922734678], predicted_final_status: 1 0 -->prob = [0.9463176785230176,0.05368232147698242], predicted_final_status: 0 0 -->prob = [0.6885079767449629,0.311492023255037], predicted_final_status: 0 1 -->prob = [0.46252434343541504,0.537475656564585], predicted_final_status: 1 0 -->prob = [0.46252434343541504,0.537475656564585], predicted_final_status: 1 1 -->prob = [0.34547046922514213,0.6545295307748579], predicted_final_status: 1 1 -->prob = [0.649720172077417,0.350279827922583], predicted_final_status: 0 0 -->prob = [0.6535813981196834,0.3464186018803167], predicted_final_status: 0 0 -->prob = [0.7199370128301507,0.28006298716984934], predicted_final_status: 0 1 -->prob = [0.40314517632560715,0.5968548236743929], predicted_final_status: 1 0 -->prob = 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predicted_final_status: 0 0 -->prob = [0.9286983003230956,0.07130169967690447], predicted_final_status: 0 0 -->prob = [0.9223033913312051,0.07769660866879499], predicted_final_status: 0 0 -->prob = [0.956344410603478,0.04365558939652211], predicted_final_status: 0 0 -->prob = [0.4652910340968865,0.5347089659031135], predicted_final_status: 1 0 -->prob = [0.9547523889819407,0.045247611018059235], predicted_final_status: 0 0 -->prob = [0.9006694023243007,0.09933059767569934], predicted_final_status: 0 0 -->prob = [0.894722697427434,0.10527730257256598], predicted_final_status: 0 0 -->prob = [0.9343020887127604,0.06569791128723951], predicted_final_status: 0 0 -->prob = [0.5131067325426846,0.4868932674573155], predicted_final_status: 0 0 -->prob = [0.45717113137445403,0.542828868625546], predicted_final_status: 1 0 -->prob = [0.8911165368734119,0.10888346312658814], predicted_final_status: 0 0 -->prob = [0.9315476227848704,0.06845237721512956], predicted_final_status: 0 0 -->prob = [0.9308294289509108,0.0691705710490891], predicted_final_status: 0 0 -->prob = [0.798532477330449,0.20146752266955104], predicted_final_status: 0 1 -->prob = [0.45717113137445403,0.542828868625546], predicted_final_status: 1 0 -->prob = [0.9313045630144497,0.06869543698555021], predicted_final_status: 0 0 -->prob = [0.9583586180887478,0.04164138191125223], predicted_final_status: 0 0 -->prob = [0.9152588014104409,0.084741198589559], predicted_final_status: 0 0 -->prob = [0.5522101885488457,0.4477898114511543], predicted_final_status: 0 0 -->prob = [0.9091073583144215,0.09089264168557844], predicted_final_status: 0 0 -->prob = [0.8811477233623363,0.1188522766376637], predicted_final_status: 0 0 -->prob = [0.9607733798595242,0.03922662014047584], predicted_final_status: 0 0 -->prob = [0.5332606931037582,0.46673930689624177], predicted_final_status: 0 0 -->prob = [0.9506140764011191,0.049385923598880895], predicted_final_status: 0 0 -->prob = [0.5128542300393971,0.4871457699606029], predicted_final_status: 0 0 -->prob = [0.9286983003230956,0.07130169967690447], predicted_final_status: 0 0 -->prob = [0.9105334586417546,0.08946654135824539], predicted_final_status: 0 0 -->prob = [0.9351166960889007,0.06488330391109928], predicted_final_status: 0 0 -->prob = [0.9507758160170028,0.049224183982997334], predicted_final_status: 0 0 -->prob = [0.9414636222993776,0.058536377700622366], predicted_final_status: 0 0 -->prob = [0.9145191532598366,0.08548084674016336], predicted_final_status: 0 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0 0 -->prob = [0.9483610542462262,0.051638945753773716], predicted_final_status: 0 1 -->prob = [0.4111854479221419,0.588814552077858], predicted_final_status: 1 0 -->prob = [0.931456327414567,0.06854367258543306], predicted_final_status: 0 0 -->prob = [0.9084353539283981,0.0915646460716019], predicted_final_status: 0 0 -->prob = [0.9547076380975748,0.045292361902425325], predicted_final_status: 0 0 -->prob = [0.9234797159279935,0.07652028407200637], predicted_final_status: 0 0 -->prob = [0.9393555650012418,0.060644434998758115], predicted_final_status: 0 0 -->prob = [0.912087602665551,0.08791239733444906], predicted_final_status: 0 0 -->prob = [0.6320191832640807,0.3679808167359192], predicted_final_status: 0 0 -->prob = [0.9536629931345433,0.04633700686545679], predicted_final_status: 0 0 -->prob = [0.8765086696347447,0.12349133036525535], predicted_final_status: 0 0 -->prob = [0.7801052973872473,0.21989470261275273], predicted_final_status: 0 0 -->prob = [0.9105334586417546,0.08946654135824539], predicted_final_status: 0 0 -->prob = [0.9082927509382813,0.09170724906171868], predicted_final_status: 0 0 -->prob = [0.9029928251455577,0.09700717485444235], predicted_final_status: 0 0 -->prob = [0.9553317519011302,0.044668248098869864], predicted_final_status: 0 0 -->prob = [0.9089673773344072,0.09103262266559273], predicted_final_status: 0 0 -->prob = [0.909448888147846,0.09055111185215403], predicted_final_status: 0 0 -->prob = [0.9151604911236811,0.08483950887631883], predicted_final_status: 0 0 -->prob = [0.9619295170690888,0.038070482930911226], predicted_final_status: 0 0 -->prob = [0.9375314578596772,0.0624685421403229], predicted_final_status: 0 0 -->prob = [0.9607733798595242,0.03922662014047584], predicted_final_status: 0 0 -->prob = [0.9547076380975748,0.045292361902425325], predicted_final_status: 0 0 -->prob = [0.9304382187953688,0.06956178120463109], predicted_final_status: 0 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0 0 -->prob = [0.9089673773344072,0.09103262266559273], predicted_final_status: 0 0 -->prob = [0.9571223998683511,0.042877600131648944], predicted_final_status: 0 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0 0 -->prob = [0.9344201255226139,0.06557987447738614], predicted_final_status: 0 0 -->prob = [0.9152588014104409,0.084741198589559], predicted_final_status: 0 0 -->prob = [0.9320227568484093,0.06797724315159068], predicted_final_status: 0 0 -->prob = [0.9298544375326602,0.07014556246733986], predicted_final_status: 0 0 -->prob = [0.9380969404400302,0.061903059559969886], predicted_final_status: 0 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0 0 -->prob = [0.9483610542462262,0.051638945753773716], predicted_final_status: 0 0 -->prob = [0.9547076380975748,0.045292361902425325], predicted_final_status: 0 0 -->prob = [0.9089673773344072,0.09103262266559273], predicted_final_status: 0 0 -->prob = [0.9464267611576943,0.05357323884230558], predicted_final_status: 0 0 -->prob = [0.9156725158654299,0.0843274841345701], predicted_final_status: 0 0 -->prob = [0.9575005478130425,0.042499452186957484], predicted_final_status: 0 0 -->prob = [0.46204331998399956,0.5379566800160005], predicted_final_status: 1 0 -->prob = [0.874330661906462,0.12566933809353792], predicted_final_status: 0 0 -->prob = [0.9089673773344072,0.09103262266559273], predicted_final_status: 0 0 -->prob = [0.8629544299135473,0.13704557008645274], predicted_final_status: 0 0 -->prob = [0.9315274748162372,0.06847252518376276], predicted_final_status: 0 0 -->prob = [0.9449658157151319,0.05503418428486816], predicted_final_status: 0 0 -->prob = [0.9456368345376935,0.05436316546230644], predicted_final_status: 0 0 -->prob = [0.9277759207528066,0.07222407924719348], predicted_final_status: 0 0 -->prob = [0.9582785370779157,0.041721462922084306], predicted_final_status: 0 0 -->prob = [0.9091073583144215,0.09089264168557844], predicted_final_status: 0 0 -->prob = [0.935310897286473,0.06468910271352704], predicted_final_status: 0 0 -->prob = [0.9126183573255803,0.08738164267441964], predicted_final_status: 0 0 -->prob = [0.9086499454438242,0.09135005455617586], predicted_final_status: 0 0 -->prob = [0.9342586258131954,0.06574137418680452], predicted_final_status: 0 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0 0 -->prob = [0.9351166960889007,0.06488330391109928], predicted_final_status: 0 0 -->prob = [0.9547076380975748,0.045292361902425325], predicted_final_status: 0 0 -->prob = [0.9583586180887478,0.04164138191125223], predicted_final_status: 0 0 -->prob = [0.933954116476005,0.06604588352399494], predicted_final_status: 0 0 -->prob = [0.9367168504835369,0.06328314951646313], predicted_final_status: 0 0 -->prob = [0.8736049153635707,0.12639508463642946], predicted_final_status: 0 0 -->prob = [0.8379969006246769,0.16200309937532303], predicted_final_status: 0 0 -->prob = [0.9081775617808724,0.09182243821912754], predicted_final_status: 0 0 -->prob = [0.9513900059470666,0.048609994052933383], predicted_final_status: 0 0 -->prob = [0.9149358455076655,0.08506415449233443], predicted_final_status: 0 0 -->prob = [0.8654318721544284,0.13456812784557165], predicted_final_status: 0 0 -->prob = [0.42100783030773725,0.5789921696922627], predicted_final_status: 1 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0 0 -->prob = [0.684953056734105,0.31504694326589494], predicted_final_status: 0 0 -->prob = [0.9119365328075633,0.08806346719243673], predicted_final_status: 0 0 -->prob = [0.9313045630144497,0.06869543698555021], predicted_final_status: 0 0 -->prob = [0.909448888147846,0.09055111185215403], predicted_final_status: 0 0 -->prob = [0.9041575910304532,0.09584240896954682], predicted_final_status: 0 0 -->prob = [0.9290881065435684,0.07091189345643162], predicted_final_status: 0 0 -->prob = [0.9350421163108683,0.06495788368913166], predicted_final_status: 0 0 -->prob = [0.9418214408304472,0.05817855916955287], predicted_final_status: 0 0 -->prob = [0.4743988158872742,0.5256011841127257], predicted_final_status: 1 0 -->prob = [0.9355172503744071,0.06448274962559278], predicted_final_status: 0 0 -->prob = [0.9351166960889007,0.06488330391109928], predicted_final_status: 0 0 -->prob = [0.9370563237961382,0.06294367620386179], predicted_final_status: 0 0 -->prob = [0.9351166960889007,0.06488330391109928], predicted_final_status: 0 0 -->prob = [0.9304382187953688,0.06956178120463109], predicted_final_status: 0 0 -->prob = [0.9119365328075633,0.08806346719243673], predicted_final_status: 0 0 -->prob = [0.9190988385833166,0.08090116141668324], predicted_final_status: 0 0 -->prob = [0.9152588014104409,0.084741198589559], predicted_final_status: 0 0 -->prob = [0.5436842690584103,0.4563157309415898], predicted_final_status: 0 0 -->prob = [0.9102634955239862,0.0897365044760138], predicted_final_status: 0 0 -->prob = [0.9323431967406423,0.06765680325935768], predicted_final_status: 0 0 -->prob = [0.9082927509382813,0.09170724906171868], predicted_final_status: 0 0 -->prob = [0.929322414126651,0.07067758587334903], predicted_final_status: 0 0 -->prob = [0.9464287669847156,0.053571233015284325], predicted_final_status: 0 0 -->prob = [0.9109314654559864,0.08906853454401366], predicted_final_status: 0 0 -->prob = [0.9066180167656128,0.09338198323438722], predicted_final_status: 0 0 -->prob = [0.9414636222993776,0.058536377700622366], predicted_final_status: 0 0 -->prob = [0.9392305869166775,0.06076941308332253], predicted_final_status: 0 0 -->prob = [0.9565903764623419,0.043409623537658114], predicted_final_status: 0 0 -->prob = [0.9369408032304655,0.0630591967695345], predicted_final_status: 0
In [162]:
# Random Forest Evalution
from pyspark.ml.evaluation import MulticlassClassificationEvaluator,BinaryClassificationEvaluator
# Select (prediction, true label) and compute test error
evaluator = MulticlassClassificationEvaluator(labelCol="indexedLabel", predictionCol="prediction", metricName="accuracy")
rf_accuracy = evaluator.evaluate(Predictions)
print("Test Error = %g" % (1.0 - rf_accuracy))
print("Test Accuracy = %g" % rf_accuracy)
rfModel = PipelineModel.stages[1]
print(rfModel) # summary only
evaluator = BinaryClassificationEvaluator(rawPredictionCol='prediction', labelCol='indexedLabel', metricName='areaUnderROC')
rf_roc = evaluator.evaluate(Predictions)
print("Test ROC = %g" %rf_roc)
rf_pr = evaluator.evaluate(Predictions, {evaluator.metricName: "areaUnderPR"})
print("Test PR = %g" %rf_pr)
Test Error = 0.152032 Test Accuracy = 0.847968 RandomForestClassificationModel (uid=RandomForestClassifier_402f9568af43d193e268) with 10 trees Test ROC = 0.84133 Test PR = 0.696162
In [160]:
# Decision Tree Model
from pyspark.ml.classification import DecisionTreeClassifier
from pyspark.ml import Pipeline
startTime = time.time()
labelIndexer = StringIndexer(inputCol="final_status", outputCol="indexedLabel").fit(trainKickstarter)
trainingData, testData = trainKickstarter.randomSplit([0.7, 0.3])
dt = DecisionTreeClassifier(labelCol="indexedLabel", featuresCol="features")
labelConverter = IndexToString(inputCol="prediction", outputCol="predictedLabel",labels=labelIndexer.labels)
pipeline = Pipeline(stages=[labelIndexer,dt,labelConverter])
PipelineModel = pipeline.fit(trainingData)
endTime = time.time()
executeTime = endTime - startTime
print ('Execution Time For Decision Tree = %s' % str(executeTime) + ' Seconds\n')
Predictions = PipelineModel.transform(testData)
Predictions.select("predictedLabel", "final_status").show(10)
preRel = Predictions.select("predictedLabel", "final_status", "features", "probability").collect()
print('''final_status --> prob = [prob_0,prob_1], predicted_final_status''')
for item in preRel:
print(str(item['final_status'])+' -->prob= '+str(item['probability'])+',predicted_final_status: '+str(item['predictedLabel']))
Execution Time For Decision Tree = 8.759777069091797 Seconds +--------------+------------+ |predictedLabel|final_status| +--------------+------------+ | 0| 0| | 1| 1| | 1| 0| | 1| 1| | 0| 0| | 1| 1| | 1| 1| | 0| 1| | 1| 1| | 1| 1| +--------------+------------+ only showing top 10 rows final_status --> prob = [prob_0,prob_1], predicted_final_status 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 0 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.8884540117416829,0.11154598825831702],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.8884540117416829,0.11154598825831702],predicted_final_status: 0 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 0 -->prob= [0.8884540117416829,0.11154598825831702],predicted_final_status: 0 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.08166089965397924,0.9183391003460207],predicted_final_status: 1 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 1 -->prob= [0.08166089965397924,0.9183391003460207],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 0 -->prob= [0.8884540117416829,0.11154598825831702],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.24886316659776767,0.7511368334022324],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 0 -->prob= [0.9843662758235623,0.015633724176437745],predicted_final_status: 0 1 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 1 -->prob= [0.09580838323353294,0.9041916167664671],predicted_final_status: 1 1 -->prob= [0.23934426229508196,0.760655737704918],predicted_final_status: 1 1 -->prob= [0.09705113848450915,0.9029488615154908],predicted_final_status: 1 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= [0.5703125,0.4296875],predicted_final_status: 0 0 -->prob= 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[0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9861173309449172,0.013882669055082848],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9861173309449172,0.013882669055082848],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9640923339982901,0.03590766600170989],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.8153660498793243,0.1846339501206758],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.7779868297271872,0.22201317027281278],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.33375796178343947,0.6662420382165605],predicted_final_status: 1 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9837817913748618,0.016218208625138224],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9861173309449172,0.013882669055082848],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.8153660498793243,0.1846339501206758],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9861173309449172,0.013882669055082848],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.8153660498793243,0.1846339501206758],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9861173309449172,0.013882669055082848],predicted_final_status: 0 0 -->prob= [0.8153660498793243,0.1846339501206758],predicted_final_status: 0 0 -->prob= [0.33375796178343947,0.6662420382165605],predicted_final_status: 1 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.8153660498793243,0.1846339501206758],predicted_final_status: 0 0 -->prob= [0.33375796178343947,0.6662420382165605],predicted_final_status: 1 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9640923339982901,0.03590766600170989],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.33375796178343947,0.6662420382165605],predicted_final_status: 1 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0 0 -->prob= [0.9977111378360554,0.002288862163944602],predicted_final_status: 0
In [154]:
# Predictions.select("predictedLabel",'final_status',"goal","key", "disable_communication",'country', "lasting_time", "backers").write.format("csv").save("rf_res.csv")
sqlContext.registerDataFrameAsTable(Predictions, "tb1")
temp = sqlContext.sql("SELECT predictedLabel,final_status,goal,key,disable_communication,country,lasting_time,backers from tb1 WHERE final_status=1 ORDER BY goal desc")
temp.show(50)
# temp = sqlContext.sql("SELECT predictedLabel,final_status,goal,key,disable_communication,country,lasting_time,backers from tb1 WHERE final_status=0 ORDER BY backers desc")
# temp.show(50)
+--------------+------------+---------+--------------------+---------------------+-------+------------+-------+ |predictedLabel|final_status| goal| key|disable_communication|country|lasting_time|backers| +--------------+------------+---------+--------------------+---------------------+-------+------------+-------+ | 1| 1|1000000.0|pathfinder-online...| 1.0| US| 4168656.0| 8732.0| | 1| 1|1000000.0|arkyd-a-space-tel...| 1.0| US| 2801287.0|17614.0| | 1| 1| 850000.0|dreamfall-chapter...| 1.0| US| 2588400.0|21858.0| | 1| 1| 600000.0|underworld-ascendant| 1.0| US| 2592000.0|13987.0| | 1| 1| 500000.0|two-guys-spaceven...| 1.0| US| 3024000.0|10809.0| | 1| 1| 500000.0|mono-the-future-o...| 1.0| DK| 2592000.0| 855.0| | 1| 1| 450000.0|rest-the-worlds-m...| 1.0| DK| 3459600.0| 2749.0| | 1| 1| 400000.0|broken-sword-the-...| 1.0| US| 2592000.0|14032.0| | 1| 1| 400000.0|divinity-original...| 1.0| US| 2592000.0|19541.0| | 1| 1| 400000.0|unveiling-the-san...| 1.0| SE| 2975516.0| 321.0| | 1| 1| 400000.0|what-we-do-in-the...| 1.0| US| 2505600.0| 7204.0| | 1| 1| 400000.0|the-mini-mobile-r...| 1.0| US| 2592000.0| 3081.0| | 1| 1| 375000.0|thimbleweed-park-...| 1.0| US| 2592000.0|15623.0| | 1| 1| 350000.0|jodorowskys-new-f...| 1.0| US| 3020400.0| 3518.0| | 1| 1| 350000.0|jagged-alliance-f...| 1.0| US| 2636949.0| 7167.0| | 1| 1| 320000.0|the-gamers-hands-...| 1.0| US| 4492924.0| 4311.0| | 1| 1| 320000.0| the-universim| 1.0| US| 2678400.0|11617.0| | 1| 1| 300000.0|bridegroom-an-ame...| 1.0| US| 2592000.0| 6508.0| | 1| 1| 300000.0|hex-mmo-trading-c...| 1.0| US| 2592000.0|17765.0| | 1| 1| 300000.0|freewavz-smart-ea...| 1.0| US| 3888000.0| 1591.0| | 1| 1| 250000.0|oculus-rift-step-...| 1.0| US| 2646517.0| 9522.0| | 1| 1| 250000.0| yogventures| 1.0| US| 2592000.0|13647.0| | 1| 1| 250000.0|radiotopia-a-stor...| 1.0| US| 2708771.0|21808.0| | 1| 1| 250000.0|ghostbusters-the-...| 1.0| US| 2588400.0| 8396.0| | 1| 1| 250000.0|gramofon-modern-c...| 1.0| US| 2592000.0| 4883.0| | 1| 1| 250000.0|leikr-the-new-dan...| 1.0| US| 2592000.0| 801.0| | 1| 1| 250000.0|m2057-by-maria-pi...| 1.0| US| 3888000.0| 624.0| | 1| 1| 250000.0|blue-laser-lamp-w...| 1.0| US| 5184000.0| 7367.0| | 1| 1| 250000.0|ownphones-the-wor...| 1.0| US| 3456000.0| 3526.0| | 1| 1| 250000.0|odin-android-smar...| 1.0| US| 3513882.0| 561.0| | 1| 1| 233626.0|capture-the-momen...| 1.0| DK| 2595600.0| 771.0| | 1| 1| 217500.0|cinefex-classic-c...| 1.0| US| 2474655.0| 1817.0| | 1| 1| 200000.0|crowdsourced-hard...| 1.0| US| 2588400.0| 5423.0| | 1| 1| 200000.0|armello-bringing-...| 1.0| AU| 2592000.0| 6213.0| | 1| 1| 200000.0|dude-bro-party-ma...| 1.0| US| 2937084.0| 4789.0| | 1| 1| 200000.0| la-mulana-2| 1.0| US| 2851200.0| 5200.0| | 1| 1| 200000.0| animusic-3-dvd| 1.0| US| 2592000.0| 3284.0| | 1| 1| 200000.0|be-here-now-the-a...| 1.0| US| 3888000.0| 5265.0| | 1| 1| 200000.0|embrace-the-docum...| 1.0| AU| 4583919.0| 8909.0| | 1| 1| 200000.0|kill-me-deadly-a-...| 1.0| US| 2592000.0| 1744.0| | 1| 1| 200000.0|antvr-kit-all-in-...| 1.0| US| 3456000.0| 681.0| | 1| 1| 200000.0|h-hour-worlds-eli...| 1.0| US| 2592000.0| 2772.0| | 1| 1| 200000.0|dart-the-worlds-s...| 1.0| US| 2600428.0| 4279.0| | 0| 1| 180000.0|dreams-in-thin-ai...| 1.0| DK| 2945593.0| 225.0| | 1| 1| 150000.0| identity| 1.0| CA| 2592000.0| 4218.0| | 1| 1| 150000.0|video-games-live-...| 1.0| US| 3401973.0| 3712.0| | 1| 1| 150000.0|elysian-shadows-n...| 1.0| US| 2592000.0| 2282.0| | 1| 1| 150000.0| zuli-smartplugs| 1.0| US| 2592000.0| 925.0| | 1| 1| 150000.0|murder-by-deaths-...| 1.0| US| 2634875.0| 3305.0| | 1| 1| 150000.0|99-invisible-seas...| 1.0| US| 2627895.0|11693.0| +--------------+------------+---------+--------------------+---------------------+-------+------------+-------+ only showing top 50 rows
In [146]:
# Decesion Tress Evalution
evaluator = MulticlassClassificationEvaluator(labelCol="indexedLabel", predictionCol="prediction", metricName="accuracy")
dt_accuracy = evaluator.evaluate(Predictions)
print("Test Error = %g" % (1.0 - dt_accuracy))
print("Test Accuracy = %g" % dt_accuracy)
treeModelClassifier = PipelineModel.stages[1]
print("Learned classification tree model:\n" + str(treeModelClassifier.toDebugString))
evaluator = BinaryClassificationEvaluator(rawPredictionCol='prediction', labelCol='indexedLabel', metricName='areaUnderROC')
dt_roc = evaluator.evaluate(Predictions)
print("Test ROC = %g" %dt_roc)
dt_pr = evaluator.evaluate(Predictions, {evaluator.metricName: "areaUnderPR"})
print("Test PR = %g" %dt_pr)
Test Error = 0.137617
Test Accuracy = 0.862383
Learned classification tree model:
DecisionTreeClassificationModel (uid=DecisionTreeClassifier_4755b8632d8cf6e7bd40) of depth 5 with 63 nodes
If (feature 25 <= 16.5)
If (feature 0 <= 790.0)
If (feature 25 <= 6.5)
If (feature 25 <= 2.5)
If (feature 0 <= 245.0)
Predict: 0.0
Else (feature 0 > 245.0)
Predict: 0.0
Else (feature 25 > 2.5)
If (feature 0 <= 245.0)
Predict: 0.0
Else (feature 0 > 245.0)
Predict: 0.0
Else (feature 25 > 6.5)
If (feature 0 <= 499.5)
If (feature 0 <= 245.0)
Predict: 1.0
Else (feature 0 > 245.0)
Predict: 1.0
Else (feature 0 > 499.5)
If (feature 25 <= 11.5)
Predict: 0.0
Else (feature 25 > 11.5)
Predict: 1.0
Else (feature 0 > 790.0)
If (feature 25 <= 10.5)
If (feature 25 <= 8.5)
If (feature 25 <= 4.5)
Predict: 0.0
Else (feature 25 > 4.5)
Predict: 0.0
Else (feature 25 > 8.5)
If (feature 0 <= 1810.0)
Predict: 0.0
Else (feature 0 > 1810.0)
Predict: 0.0
Else (feature 25 > 10.5)
If (feature 0 <= 1810.0)
If (feature 0 <= 1095.5)
Predict: 0.0
Else (feature 0 > 1095.5)
Predict: 0.0
Else (feature 0 > 1810.0)
If (feature 0 <= 3976.0)
Predict: 0.0
Else (feature 0 > 3976.0)
Predict: 0.0
Else (feature 25 > 16.5)
If (feature 25 <= 75.5)
If (feature 0 <= 4725.0)
If (feature 0 <= 1490.0)
If (feature 25 <= 28.5)
Predict: 1.0
Else (feature 25 > 28.5)
Predict: 1.0
Else (feature 0 > 1490.0)
If (feature 25 <= 33.5)
Predict: 0.0
Else (feature 25 > 33.5)
Predict: 1.0
Else (feature 0 > 4725.0)
If (feature 0 <= 7515.0)
If (feature 25 <= 46.5)
Predict: 0.0
Else (feature 25 > 46.5)
Predict: 0.0
Else (feature 0 > 7515.0)
If (feature 25 <= 46.5)
Predict: 0.0
Else (feature 25 > 46.5)
Predict: 0.0
Else (feature 25 > 75.5)
If (feature 0 <= 5450.0)
If (feature 25 <= 114.5)
If (feature 0 <= 3012.5)
Predict: 1.0
Else (feature 0 > 3012.5)
Predict: 1.0
Else (feature 25 > 114.5)
If (feature 25 <= 140.5)
Predict: 1.0
Else (feature 25 > 140.5)
Predict: 1.0
Else (feature 0 > 5450.0)
If (feature 25 <= 306.5)
If (feature 0 <= 24875.0)
Predict: 1.0
Else (feature 0 > 24875.0)
Predict: 0.0
Else (feature 25 > 306.5)
If (feature 0 <= 29997.5)
Predict: 1.0
Else (feature 0 > 29997.5)
Predict: 1.0
Test ROC = 0.858129
Test PR = 0.722099
In [147]:
# LogisticRegression Model
from pyspark.ml.classification import LogisticRegression
startTime = time.time()
labelIndexer = StringIndexer(inputCol="final_status", outputCol="indexedLabel").fit(trainKickstarter)
trainingData, testData = trainKickstarter.randomSplit([0.7, 0.3])
mlr = LogisticRegression().setLabelCol("indexedLabel").setFeaturesCol("features").setMaxIter(10).setFamily("multinomial")
labelConverter = IndexToString(inputCol="prediction", outputCol="predictedLabel",labels=labelIndexer.labels)
pipeline = Pipeline(stages=[labelIndexer,mlr,labelConverter])
PipelineModel = pipeline.fit(trainingData)
endTime = time.time()
executeTime = endTime - startTime
print ('Execution Time For LogisticRegression = %s' % str(executeTime) + ' Seconds\n')
Predictions = PipelineModel.transform(testData)
Predictions.select("predictedLabel", "final_status").show(10)
preRel = Predictions.select("predictedLabel", "final_status", "features", "probability").collect()
print('''final_status --> prob = [prob_0,prob_1], predicted_final_status''')
for item in preRel:
print(str(item['final_status'])+' -->prob= '+str(item['probability'])+',predicted_final_status: '+str(item['predictedLabel']))
Execution Time For LogisticRegression = 3.7279200553894043 Seconds +--------------+------------+ |predictedLabel|final_status| +--------------+------------+ | 0| 1| | 0| 1| | 0| 1| | 0| 1| | 0| 1| | 0| 1| | 0| 0| | 0| 1| | 0| 1| | 0| 1| +--------------+------------+ only showing top 10 rows final_status --> prob = [prob1,prob2], predicted_final_status 1 -->prob= [0.8002685907568968,0.1997314092431032],predicted_final_status: 0 1 -->prob= [0.7946660661212444,0.2053339338787557],predicted_final_status: 0 1 -->prob= [0.5899359422953337,0.41006405770466625],predicted_final_status: 0 1 -->prob= [0.5829643502099349,0.41703564979006513],predicted_final_status: 0 1 -->prob= [0.832013101634846,0.16798689836515387],predicted_final_status: 0 1 -->prob= [0.7887764866188092,0.2112235133811908],predicted_final_status: 0 0 -->prob= [0.8163095867526224,0.18369041324737745],predicted_final_status: 0 1 -->prob= [0.7490305126494017,0.25096948735059826],predicted_final_status: 0 1 -->prob= [0.8334877260950555,0.16651227390494444],predicted_final_status: 0 1 -->prob= [0.7559256530427506,0.24407434695724942],predicted_final_status: 0 1 -->prob= [0.7936771025259564,0.20632289747404362],predicted_final_status: 0 1 -->prob= [0.7398009697847582,0.2601990302152419],predicted_final_status: 0 0 -->prob= [0.8082163044533524,0.19178369554664776],predicted_final_status: 0 1 -->prob= [0.7099955241340135,0.29000447586598654],predicted_final_status: 0 1 -->prob= [0.7148167625852933,0.28518323741470686],predicted_final_status: 0 1 -->prob= [0.7837662074558078,0.21623379254419214],predicted_final_status: 0 1 -->prob= [0.7333211838849,0.26667881611509997],predicted_final_status: 0 1 -->prob= [0.6782382108327056,0.32176178916729437],predicted_final_status: 0 1 -->prob= [0.6479591217092395,0.3520408782907605],predicted_final_status: 0 1 -->prob= [0.6662369028231618,0.33376309717683816],predicted_final_status: 0 1 -->prob= [0.697000525974396,0.302999474025604],predicted_final_status: 0 0 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[0.8438783015869361,0.15612169841306386],predicted_final_status: 0 0 -->prob= [0.8853286868612207,0.11467131313877928],predicted_final_status: 0 0 -->prob= [0.9320890404982534,0.06791095950174658],predicted_final_status: 0 0 -->prob= [0.912481478117698,0.08751852188230197],predicted_final_status: 0 0 -->prob= [0.8864923463568952,0.11350765364310485],predicted_final_status: 0 0 -->prob= [0.8790195480426827,0.12098045195731737],predicted_final_status: 0 0 -->prob= [0.8760309137664043,0.12396908623359575],predicted_final_status: 0 0 -->prob= [0.9288349811029428,0.07116501889705708],predicted_final_status: 0 0 -->prob= [0.9428811764765761,0.05711882352342391],predicted_final_status: 0 0 -->prob= [0.8890681375013333,0.11093186249866671],predicted_final_status: 0 0 -->prob= [0.9405849875983433,0.05941501240165676],predicted_final_status: 0 0 -->prob= [0.8875838729539455,0.11241612704605461],predicted_final_status: 0 0 -->prob= [0.8968049769914761,0.10319502300852403],predicted_final_status: 0 0 -->prob= [0.9296930211774878,0.07030697882251237],predicted_final_status: 0 0 -->prob= [0.9323664120651928,0.06763358793480714],predicted_final_status: 0 0 -->prob= [0.8930004711785958,0.10699952882140414],predicted_final_status: 0 0 -->prob= [0.8712914677296827,0.12870853227031728],predicted_final_status: 0 0 -->prob= [0.891295141960041,0.10870485803995898],predicted_final_status: 0 0 -->prob= [0.85352794678868,0.14647205321131998],predicted_final_status: 0 0 -->prob= [0.8842463596184766,0.1157536403815233],predicted_final_status: 0 0 -->prob= [0.9289344429700187,0.0710655570299814],predicted_final_status: 0 0 -->prob= [0.8736912201186364,0.1263087798813636],predicted_final_status: 0 0 -->prob= [0.8856647245098422,0.11433527549015772],predicted_final_status: 0 0 -->prob= [0.15055467597590907,0.849445324024091],predicted_final_status: 1 0 -->prob= [0.9074128249589165,0.0925871750410835],predicted_final_status: 0 0 -->prob= [0.861456855194303,0.13854314480569688],predicted_final_status: 0 0 -->prob= [0.8829375702918941,0.11706242970810575],predicted_final_status: 0 0 -->prob= [0.8752537792031919,0.1247462207968081],predicted_final_status: 0 0 -->prob= [0.8332172936010916,0.16678270639890838],predicted_final_status: 0 0 -->prob= [0.9195983706490906,0.08040162935090946],predicted_final_status: 0 0 -->prob= [0.9177608277704443,0.08223917222955573],predicted_final_status: 0 0 -->prob= [0.9453349022977859,0.05466509770221396],predicted_final_status: 0 0 -->prob= [0.8847677680230724,0.11523223197692764],predicted_final_status: 0 0 -->prob= [0.8757408871052501,0.12425911289474978],predicted_final_status: 0 0 -->prob= [0.9231429835292295,0.07685701647077053],predicted_final_status: 0 0 -->prob= [3.59147284130399e-08,0.9999999640852717],predicted_final_status: 1 0 -->prob= [0.9170423200224302,0.08295767997756975],predicted_final_status: 0 0 -->prob= [0.9157543711601777,0.08424562883982226],predicted_final_status: 0 0 -->prob= [0.8837708874947158,0.11622911250528428],predicted_final_status: 0 0 -->prob= [0.8769158760472274,0.12308412395277245],predicted_final_status: 0 0 -->prob= [0.8811575088054494,0.1188424911945507],predicted_final_status: 0 0 -->prob= [0.948959485986348,0.051040514013652026],predicted_final_status: 0 0 -->prob= [0.8948105773812421,0.10518942261875797],predicted_final_status: 0 0 -->prob= [0.9259254403137603,0.0740745596862396],predicted_final_status: 0 0 -->prob= [0.8868781437580012,0.11312185624199879],predicted_final_status: 0 0 -->prob= [0.8458094841486822,0.15419051585131785],predicted_final_status: 0 1 -->prob= [2.4301528269513835e-60,1.0],predicted_final_status: 1 0 -->prob= [0.8968513519251755,0.10314864807482457],predicted_final_status: 0 0 -->prob= [0.8738767802375986,0.12612321976240143],predicted_final_status: 0 0 -->prob= [0.9267133390069036,0.07328666099309647],predicted_final_status: 0 0 -->prob= [0.9310510560384002,0.06894894396159983],predicted_final_status: 0 0 -->prob= [0.8913992850219301,0.10860071497806974],predicted_final_status: 0 0 -->prob= [0.9531670323757636,0.046832967624236395],predicted_final_status: 0 0 -->prob= [0.9510975659671744,0.048902434032825626],predicted_final_status: 0 0 -->prob= [0.9563394031726061,0.04366059682739387],predicted_final_status: 0 0 -->prob= [0.8771977167263992,0.1228022832736008],predicted_final_status: 0 0 -->prob= [0.9260853567041297,0.07391464329587022],predicted_final_status: 0 0 -->prob= [0.871774772627413,0.12822522737258693],predicted_final_status: 0 0 -->prob= [0.9239048863148221,0.07609511368517781],predicted_final_status: 0 0 -->prob= [0.5297108626282828,0.470289137371717],predicted_final_status: 0 1 -->prob= [1.7098432629966863e-51,1.0],predicted_final_status: 1 1 -->prob= [2.946331332755566e-58,1.0],predicted_final_status: 1 0 -->prob= [0.9269305687682782,0.07306943123172176],predicted_final_status: 0 0 -->prob= [0.8982908084287407,0.10170919157125932],predicted_final_status: 0 0 -->prob= [0.7857512205067583,0.21424877949324164],predicted_final_status: 0 0 -->prob= [0.21085523953129057,0.7891447604687094],predicted_final_status: 1 0 -->prob= [0.9233023084991439,0.07669769150085608],predicted_final_status: 0 0 -->prob= [0.9046262522046319,0.09537374779536817],predicted_final_status: 0 0 -->prob= [0.9184424810994614,0.0815575189005387],predicted_final_status: 0 0 -->prob= [0.9411006657436078,0.05889933425639222],predicted_final_status: 0 0 -->prob= [0.9122431740032606,0.08775682599673941],predicted_final_status: 0 0 -->prob= [0.8762872064108321,0.12371279358916794],predicted_final_status: 0 0 -->prob= [0.8990385959146409,0.1009614040853591],predicted_final_status: 0 0 -->prob= [0.931868214882153,0.06813178511784702],predicted_final_status: 0 0 -->prob= [0.9394357991981699,0.0605642008018301],predicted_final_status: 0 0 -->prob= [0.948211106918063,0.05178889308193699],predicted_final_status: 0 0 -->prob= [0.930359138565181,0.06964086143481911],predicted_final_status: 0 1 -->prob= [2.388852320781549e-62,1.0],predicted_final_status: 1 0 -->prob= [0.9659971558414876,0.03400284415851239],predicted_final_status: 0 0 -->prob= [0.9274961976279368,0.0725038023720633],predicted_final_status: 0 0 -->prob= [0.9354476269392256,0.0645523730607744],predicted_final_status: 0 0 -->prob= [0.9589821792563773,0.04101782074362284],predicted_final_status: 0 0 -->prob= [0.9317942331933808,0.06820576680661926],predicted_final_status: 0 0 -->prob= [0.9352820343262068,0.06471796567379322],predicted_final_status: 0 0 -->prob= [0.9695358351601063,0.03046416483989364],predicted_final_status: 0 0 -->prob= [0.00013211508218821647,0.9998678849178118],predicted_final_status: 1 0 -->prob= [0.9550408847397713,0.044959115260228666],predicted_final_status: 0 0 -->prob= [0.9356337085919487,0.06436629140805121],predicted_final_status: 0 0 -->prob= [0.9488249081401103,0.05117509185988955],predicted_final_status: 0 0 -->prob= [0.9325423394484145,0.0674576605515855],predicted_final_status: 0 0 -->prob= [0.9475237789330433,0.05247622106695676],predicted_final_status: 0 0 -->prob= [0.9407307337809695,0.05926926621903061],predicted_final_status: 0 0 -->prob= [0.9533355854894972,0.0466644145105028],predicted_final_status: 0 0 -->prob= [0.964425650413412,0.03557434958658805],predicted_final_status: 0 0 -->prob= [0.9812186371363003,0.01878136286369978],predicted_final_status: 0 0 -->prob= [0.9526475680752199,0.04735243192478015],predicted_final_status: 0 0 -->prob= [0.9619383707754172,0.03806162922458294],predicted_final_status: 0 0 -->prob= [0.9401402009865975,0.059859799013402534],predicted_final_status: 0 0 -->prob= [0.9686528314971484,0.03134716850285155],predicted_final_status: 0 0 -->prob= [0.948280145424286,0.051719854575713896],predicted_final_status: 0 0 -->prob= [0.9451063983339069,0.05489360166609325],predicted_final_status: 0 0 -->prob= [0.9623893297364419,0.03761067026355805],predicted_final_status: 0 0 -->prob= [0.9552259894129804,0.044774010587019644],predicted_final_status: 0 0 -->prob= [0.9852990151330746,0.014700984866925367],predicted_final_status: 0 0 -->prob= [0.8757227793121688,0.12427722068783117],predicted_final_status: 0 0 -->prob= [0.9487831161001783,0.05121688389982175],predicted_final_status: 0 0 -->prob= [0.961619080789911,0.03838091921008908],predicted_final_status: 0 0 -->prob= [0.9745435029015338,0.025456497098466202],predicted_final_status: 0 0 -->prob= [0.9628472188626008,0.03715278113739923],predicted_final_status: 0 0 -->prob= [0.9847990825027985,0.015200917497201637],predicted_final_status: 0 0 -->prob= [0.9718281329623945,0.02817186703760553],predicted_final_status: 0 0 -->prob= [0.983852669643267,0.016147330356733037],predicted_final_status: 0 0 -->prob= [0.9753818478251649,0.02461815217483522],predicted_final_status: 0 0 -->prob= [0.968029172129448,0.03197082787055221],predicted_final_status: 0 0 -->prob= [0.9629119638015009,0.03708803619849911],predicted_final_status: 0 0 -->prob= [0.9514995071063377,0.04850049289366224],predicted_final_status: 0 0 -->prob= [0.9711392481499828,0.02886075185001719],predicted_final_status: 0 0 -->prob= [0.9832587159209895,0.01674128407901067],predicted_final_status: 0 0 -->prob= [0.9925977438550528,0.007402256144947183],predicted_final_status: 0 0 -->prob= [0.9932838690221185,0.00671613097788146],predicted_final_status: 0 0 -->prob= [0.9914159717296535,0.008584028270346426],predicted_final_status: 0 0 -->prob= [0.9629625319127187,0.037037468087281235],predicted_final_status: 0 0 -->prob= [0.980674724893798,0.01932527510620199],predicted_final_status: 0 0 -->prob= [0.9752405971166331,0.02475940288336681],predicted_final_status: 0 0 -->prob= [0.9803228312934062,0.019677168706593636],predicted_final_status: 0 0 -->prob= [0.9774547187204743,0.022545281279525695],predicted_final_status: 0 0 -->prob= [0.9764369163151111,0.023563083684888783],predicted_final_status: 0 0 -->prob= [0.9853669179043842,0.014633082095615675],predicted_final_status: 0 0 -->prob= [0.9839532839335845,0.016046716066415515],predicted_final_status: 0 0 -->prob= [0.9713227359548986,0.028677264045101482],predicted_final_status: 0 0 -->prob= [0.9820434279472445,0.01795657205275554],predicted_final_status: 0 0 -->prob= [0.983030505786289,0.016969494213710974],predicted_final_status: 0 0 -->prob= [0.9865775677855644,0.013422432214435594],predicted_final_status: 0 0 -->prob= [0.9847650241528758,0.015234975847124048],predicted_final_status: 0 0 -->prob= [0.9891501536848059,0.010849846315194287],predicted_final_status: 0 0 -->prob= [0.9914257046429662,0.008574295357033739],predicted_final_status: 0 0 -->prob= [0.9920538363182551,0.00794616368174495],predicted_final_status: 0 0 -->prob= [0.991058881405684,0.008941118594316],predicted_final_status: 0 0 -->prob= [0.9949187694099104,0.00508123059008956],predicted_final_status: 0 0 -->prob= [0.9879197592074467,0.012080240792553298],predicted_final_status: 0 0 -->prob= [0.9895064118230453,0.010493588176954723],predicted_final_status: 0 0 -->prob= [0.9887222352197855,0.011277764780214606],predicted_final_status: 0 0 -->prob= [0.9957783046472913,0.004221695352708752],predicted_final_status: 0 0 -->prob= [0.9967094632688889,0.003290536731111244],predicted_final_status: 0 0 -->prob= [0.994941817785913,0.005058182214087157],predicted_final_status: 0 0 -->prob= [0.9941837084587143,0.005816291541285696],predicted_final_status: 0 0 -->prob= [0.9948326208966876,0.005167379103312456],predicted_final_status: 0 0 -->prob= [0.9963737948856487,0.003626205114351186],predicted_final_status: 0 0 -->prob= [0.9957163201053416,0.004283679894658272],predicted_final_status: 0 0 -->prob= [0.9931614270397663,0.006838572960233624],predicted_final_status: 0 0 -->prob= [0.9957590889456558,0.004240911054344222],predicted_final_status: 0 0 -->prob= [5.3366630460781e-06,0.9999946633369539],predicted_final_status: 1 0 -->prob= [0.9981691057133083,0.001830894286691689],predicted_final_status: 0 0 -->prob= [0.9974944647891966,0.0025055352108033163],predicted_final_status: 0 0 -->prob= [0.9987809597864912,0.0012190402135088831],predicted_final_status: 0 0 -->prob= [0.9992919291783451,0.0007080708216548992],predicted_final_status: 0 0 -->prob= [0.9997507237045918,0.0002492762954081549],predicted_final_status: 0 0 -->prob= [0.9999370886933073,6.291130669276374e-05],predicted_final_status: 0 0 -->prob= [0.999874365236552,0.00012563476344802597],predicted_final_status: 0 0 -->prob= [0.9998910482764123,0.0001089517235877045],predicted_final_status: 0 0 -->prob= [0.9999903022646421,9.697735357892794e-06],predicted_final_status: 0 0 -->prob= [0.9999862139800212,1.3786019978779878e-05],predicted_final_status: 0 0 -->prob= [0.9999847172858369,1.5282714162991033e-05],predicted_final_status: 0 0 -->prob= [0.9999994687325153,5.312674846822837e-07],predicted_final_status: 0 0 -->prob= [0.9999999800760613,1.992393885402233e-08],predicted_final_status: 0 0 -->prob= [0.9999999750262891,2.4973710986740076e-08],predicted_final_status: 0 0 -->prob= [0.9999999693088732,3.06911266321288e-08],predicted_final_status: 0 0 -->prob= [0.9999999582907553,4.1709244680013374e-08],predicted_final_status: 0 0 -->prob= [0.9999999924337121,7.56628807536376e-09],predicted_final_status: 0 0 -->prob= [0.9999999999997846,2.1544593007446947e-13],predicted_final_status: 0 0 -->prob= [0.9999999999999998,1.5289015118705038e-16],predicted_final_status: 0 0 -->prob= [1.0,6.023986069537276e-19],predicted_final_status: 0 0 -->prob= [1.0,4.453772136681522e-22],predicted_final_status: 0 0 -->prob= [1.0,3.182563432725674e-36],predicted_final_status: 0 0 -->prob= [1.0,4.105308995879175e-36],predicted_final_status: 0 0 -->prob= [1.0,5.292824786302929e-50],predicted_final_status: 0
In [148]:
# LogisticRegression Evalution
evaluator = MulticlassClassificationEvaluator(labelCol="indexedLabel", predictionCol="prediction", metricName="accuracy")
lg_accuracy = evaluator.evaluate(Predictions)
print("Test Error = %g" % (1.0 - lg_accuracy))
print("Test Accuracy = %g" % lg_accuracy)
mlrModel = PipelineModel.stages[1]
print("Multinomial coefficients: " +str(mlrModel.coefficientMatrix)+"\nMultinomial intercepts: "+str(mlrModel.interceptVector)+"\nNumClasses: "+str(mlrModel.numClasses)+"\nnumFeatures: "+str(mlrModel.numFeatures))
trainingSummary = mlrModel.summary
print(trainingSummary.areaUnderROC)
fMeasure = trainingSummary.fMeasureByThreshold
maxFMeasure = fMeasure.groupBy().max('F-Measure').select('max(F-Measure)').head()
bestThreshold = fMeasure.where(fMeasure['F-Measure'] == maxFMeasure['max(F-Measure)']).select('threshold').head()['threshold']
mlr.setThreshold(bestThreshold)
evaluator = BinaryClassificationEvaluator(rawPredictionCol='prediction', labelCol='indexedLabel', metricName='areaUnderROC')
lg_roc = evaluator.evaluate(Predictions)
print("Test ROC = %g" %lg_roc)
lg_pr = evaluator.evaluate(Predictions, {evaluator.metricName: "areaUnderPR"})
print("Test PR = %g" %lg_pr)
Test Error = 0.247289
Test Accuracy = 0.752711
Multinomial coefficients: DenseMatrix([[ 7.97716579e-07, 7.56392457e-04, -1.99648155e-02,
2.31001326e-02, 3.61353932e-03, -4.63745512e-03,
-4.38599373e-02, -2.47731312e-02, -4.63360850e-02,
-1.64387176e-02, 1.29108940e-02, -8.82864150e-03,
0.00000000e+00, 4.38170286e-02, 5.46043769e-02,
1.09365373e-01, 0.00000000e+00, 1.87552420e+00,
0.00000000e+00, 4.49077996e-02, 0.00000000e+00,
0.00000000e+00, 1.21999029e-01, 1.25183593e-01,
9.46921269e-08, -4.26051227e-03],
[-7.97716579e-07, -7.56392457e-04, 1.99648155e-02,
-2.31001326e-02, -3.61353932e-03, 4.63745512e-03,
4.38599373e-02, 2.47731312e-02, 4.63360850e-02,
1.64387176e-02, -1.29108940e-02, 8.82864150e-03,
0.00000000e+00, -4.38170286e-02, -5.46043769e-02,
-1.09365373e-01, 0.00000000e+00, -1.87552420e+00,
0.00000000e+00, -4.49077996e-02, 0.00000000e+00,
0.00000000e+00, -1.21999029e-01, -1.25183593e-01,
-9.46921269e-08, 4.26051227e-03]])
Multinomial intercepts: [0.4081748967811718,-0.4081748967811718]
NumClasses: 2
numFeatures: 26
0.8438296437160347
Test ROC = 0.630822
Test PR = 0.640753
In [ ]:
# LogisticRegression CrossValidation
from pyspark.ml.tuning import CrossValidator, ParamGridBuilder
paramGrid = ParamGridBuilder().addGrid(mlr.elasticNetParam, [0.0,0.2,0.8]).addGrid(mlr.regParam, [0.0,0.01, 0.1, 0.5]).build()
cv = CrossValidator().setEstimator(pipeline).setEvaluator(MulticlassClassificationEvaluator().setLabelCol("indexedLabel").setPredictionCol("prediction")).setEstimatorParamMaps(paramGrid).setNumFolds(3)
cvModel = cv.fit(trainingData)
Predictions=cvModel.transform(testData)
preRel = Predictions.select("predictedLabel", "final_status", "features", "probability").collect()
print('''final_status --> prob = [prob_0,prob_1], predicted_final_status''')
for item in preRel:
print(str(item['final_status'])+' -->prob= '+str(item['probability'])+',predicted_final_status: '+str(item['predictedLabel']))
In [ ]:
evaluator = MulticlassClassificationEvaluator().setLabelCol("indexedLabel").setPredictionCol("prediction")
lrAccuracy = evaluator.evaluate(Predictions)
print(lrAccuracy)
bestModel= cvModel.bestModel
lrModel = bestModel.stages[1]
print("Coefficients: " + str(lrModel.coefficientMatrix) + "Intercept: "+str(lrModel.interceptVector)+ "numClasses: "+str(lrModel.numClasses)+"numFeatures: "+str(lrModel.numFeatures))
# print(bestModel.extractParamMap()[lrModel.getParam('elasticNetParam')])
print(mlr.explainParam(mlr.regParam))
print(mlr.explainParam(mlr.elasticNetParam))
In [76]:
# Naive Bayes Model
from pyspark.ml.classification import NaiveBayes
startTime = time.time()
labelIndexer = StringIndexer(inputCol="final_status", outputCol="indexedLabel").fit(trainKickstarter)
trainingData, testData = trainKickstarter.randomSplit([0.7, 0.3])
nb = NaiveBayes(featuresCol='features', labelCol='indexedLabel',smoothing=1.0, modelType='multinomial')
labelConverter = IndexToString(inputCol="prediction", outputCol="predictedLabel",labels=labelIndexer.labels)
pipeline = Pipeline(stages=[labelIndexer,nb,labelConverter])
PipelineModel = pipeline.fit(trainingData)
endTime = time.time()
executeTime = endTime - startTime
print ('Execution Time For NaiveBayes = %s' % str(executeTime) + ' Seconds\n')
Predictions = PipelineModel.transform(testData)
Predictions.select("predictedLabel", "final_status").show(10)
preRel = Predictions.select("predictedLabel", "final_status", "features", "probability").collect()
print('''final_status --> prob = [prob1,prob2], predicted_final_status''')
for item in preRel:
print(str(item['final_status'])+' -->prob= '+str(item['probability'])+',predicted_final_status: '+str(item['predictedLabel']))
Execution Time For NaiveBayes = 4.693087816238403 Seconds +--------------+------------+ |predictedLabel|final_status| +--------------+------------+ | 1| 1| | 1| 0| | 1| 0| | 1| 1| | 1| 1| | 1| 1| | 1| 1| | 1| 0| | 1| 0| | 1| 1| +--------------+------------+ only showing top 10 rows final_status --> prob = [prob1,prob2], predicted_final_status 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= [0.0,1.0],predicted_final_status: 1 1 -->prob= [0.0,1.0],predicted_final_status: 1 0 -->prob= 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[1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 1 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0 0 -->prob= [1.0,0.0],predicted_final_status: 0
In [77]:
# Naive Bayes Evalution
evaluator = MulticlassClassificationEvaluator(labelCol="indexedLabel", predictionCol="prediction", metricName="accuracy")
nb_accuracy = evaluator.evaluate(Predictions)
print("Test Error = %g" % (1.0 - nb_accuracy))
print("Test Accuracy = %g" % nb_accuracy)
nbModel = PipelineModel.stages[1]
print(nbModel)
evaluator = BinaryClassificationEvaluator(rawPredictionCol='prediction', labelCol='indexedLabel', metricName='areaUnderROC')
nb_roc = evaluator.evaluate(Predictions)
print("Test ROC = %g" %nb_roc)
nb_pr = evaluator.evaluate(Predictions, {evaluator.metricName: "areaUnderPR"})
print("Test PR = %g" %nb_pr)
Test Error = 0.582895 Test Accuracy = 0.417105 NaiveBayes_48f9b1204963939d0e75 Test ROC = 0.551889 Test PR = 0.344063
In [82]:
import plotly
import plotly.plotly as py
import plotly.graph_objs as go
plotly.tools.set_credentials_file(username='Charonnnnn', api_key='AbJWgmkkFaenpmi0reYX')
accuracy_ = go.Bar(
x=['RandomForest', 'DecisionTree', 'LogisticRegression', 'NaiveBayes'],
y=[rf_accuracy,dt_accuracy,lg_accuracy,nb_accuracy],
name='Accuracy',
marker=dict(
color='rgb(242,156,177)'
)
)
roc_ = go.Bar(
x=['RandomForest', 'DecisionTree', 'LogisticRegression', 'NaiveBayes'],
y=[rf_roc,dt_roc,lg_roc,nb_roc],
name='ROC',
marker=dict(
color='#FAFAD2',
)
)
pr_ = go.Bar(
x=['RandomForest', 'DecisionTree', 'LogisticRegression', 'NaiveBayes'],
y=[rf_pr,dt_pr,lg_pr,nb_pr],
name='PR',
marker=dict(
color='#FFE1FF',
)
)
data = [accuracy_, roc_, pr_]
layout = go.Layout(
xaxis=dict(tickangle=-45),
barmode='group',
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='angled-text-bar')
High five! You successfully sent some data to your account on plotly. View your plot in your browser at https://plot.ly/~Charonnnnn/0 or inside your plot.ly account where it is named 'angled-text-bar'
Out[82]:
In [137]:
from wordcloud import WordCloud,STOPWORDS
# from nltk.stem.porter import PorterStemmer
from ast import literal_eval
def tokenize(text):
# stemmeren = PorterStemmer()
lowercase = [tkn.lower() for tkn in text]
stop_rm = [wd for wd in lowercase if not wd in STOPWORDSEN]
# stem = [stemmeren.stem(wd) for wd in stop_rm]
return [j for j in stop_rm if j]
# load stop words list
stopWordsSet = sc.textFile("stop-word-list.txt").collect()
STOPWORDSEN = set(stopWordsSet)
with open('data_keywords.txt','r') as f:
fd = f.read()
res = literal_eval(fd)
res = tokenize(res)
length = len(res)
print(length)
# print(type(res))
# Read the whole text.
# Generate a word cloud image
wordcloud = WordCloud(stopwords=STOPWORDS,width=1200,height=600,scale=1.5).generate_from_text(','.join(res))
# Display the generated image:
# the matplotlib way:
import matplotlib.pyplot as plt
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.show()
# The pil way (if you don't have matplotlib)
# image = wordcloud.to_image()
# image.show()
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